• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.497-503
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• 2021

The aim of this study is to determine the factors that affect customer satisfaction in the banking sector of Bangladesh because the economic growth and stability of a country depends on the soundness of its banking sector. The study tries to investigate and assess the quality of service on customer satisfaction in the banking sector. As a sample, data were collected from 382 respondents who were customers of 32 selected commercial banks of Bangladesh. A pre-structured questionnaire was used to collect the required data and information. OLS regression model and descriptive statistical tools were used to analyze data. The results of this study reveal that the quality of service (e.g., tangibility, reliability, and empathy) has a statistically significant impact on customer satisfaction. The results also show that there is a positive correlation between the customer satisfaction and service quality dimensions in the banking sector of Bangladesh. The present study finds that in the domestic banking industry the service quality dimensions (i.e., tangibility, reliability, and empathy) have significant positive impact on customer satisfaction. The findings of the present study suggest that Bank Supervisory Authority, Central Bank of Bangladesh, and Bank Management should give special emphasis to ensure maximum satisfaction of banks' customers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.1-9
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• 2008

The Logistic cone is studied as a most desirable for the software testing effort. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, a software-reliability growth model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. After defining a software reliability, This paper discusses the relations between testing time and reliability and between duration following failure fixing and reliability are studied SRGM in several literatures has used the exponential curve, Railleigh curve or Weibull cure as an amount of testing effort during software testing phase. However, it might not be appropriate to represent the consumption curve for testing effort by one of already proposed curves in some software development environments. Therefore, this paper shows that a logistic testing- effort function can be adequately expressed as a software development/testing effort curve and that it gives a good predictive capability based on real failure data.

• Industry Promotion Research
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• v.7 no.3
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• pp.9-16
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• 2022

In the midst of increasing interest in the environmental responsibility of companies, this study investigates how eco-friendly activities affect the creation of management performance. To this end, the effect of companies' green marketing on consumers' word-of-mouth intention, the mediating effect of brand reliability, and the moderating effect of consumers' pro-environmental behavior were verified. The results of the collected data analysis are as follows. First, companies' green marketing has a positive (+) effect on consumers' word-of-mouth intention. Second, brand reliability takes a positive (+) mediating role in the relationship between companies' green marketing and consumers' word-of-mouth intention. Third, consumers' pro-environment behavior has a moderating role between Brand Reliability and their word-of-mouth intention. Therefore, companies' eco-friendly strategies and their implementation will help enhance both brand reliability and consumers' word-of-mouth intention. By revealing the effect of companies' eco-friendly strategies and their implementation on brand reliability and consumers' word-of-mouth intention it is meaningful to analyze the relationship between green marketing and the possibility of consumers' spontaneous word-of-mouth intention. The results suggest to companies that it is necessary to establish an eco-friendly marketing strategy for sustainable growth.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.5
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• pp.61-73
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• 2009

Many software reliability growth models(SRGM) have been proposed since the software reliability issue was raised in 1972. The technology to estimate and grow the reliability of developing S/W to target value during testing phase were developed using them. Most of these propositions assumed the S/W debugging testing efforts be constant or even did not consider them. A few papers were presented as the software reliability evaluation considering the testing effort was important afterwards. The testing effort forms which have been presented by this kind of papers were exponential, Rayleigh, Weibull, or Logistic functions, and one of these 4 types was used as a testing effort function depending on the S/W developing circumstances. I propose the methology to evaluate the SRGM using least square estimater and maximum likelihood estimater for those 4 functions, and then examine parameters applying actual data adopted from real field test of developing S/W.

• The Transactions of the Korea Information Processing Society
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• v.5 no.10
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• pp.2575-2583
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• 1998

The productionof the highly relible softwae systems and theirs performance evaluation hae become important interests in the software industry. The software evaluation has been mainly carried out in ternns of both reliability and performance of software system. Software reliability is the probability that no software error occurs for a fixed time interval during software testing phase. These theoretical software reliability models are sometimes unsuitable for the practical testing phase in which a software error at a certain testing stage occurs by causes of the imperfect debugging, abnornal software correction, and so on. Such a certatin software testing stage needs to be considered as an outlying stage. And we can assume that the software reliability does not improve by means of muisance factor in this outlying testing stage. In this paper, we discuss Bavesian software reliability growth modeling and estimation procedure in the presence of an imidentitied outlying software testing stage by the modification of Jehnski Moranda. Also we derive the Bayes estimaters of the software reliability panmeters by the assumption of prior information under the squared error los function. In addition, we evaluate the proposed software reliability growth model with an unidentified outlying stage in an exchangeable model according to the values of nuisance paramether using the accuracy, bias, trend, noise metries as the quantilative evaluation criteria through the compater simulation.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3490-3499
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• 1999

The hyper-geometric distribution software reliability growth model (HGDM) was recently developed and successfully applied to the problem of estimating the number of initial faults residual in a software at the beginning of the test-and-debug phase. Though the HGDM is a time-domain software reliability growth model(SRGM), it is not possible to compare the HGDM with other time-domain SRGMs. Furthermore the usual software reliability can not be computed. These drawbacks are derived from fact that the HGDM is not described in terms of the execution time. Thus we develop a continuous-time HGDM with binomial sensitivity factor in order to remove these drawbacks. Statistical characteristics of the suggested model are studied and its applicability is then examined by analyzing real test data sets. It is empirically shown that the continuous-time HGDM with binomial sensitivity factor can be used as an alternative to the current HGDM.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.2
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• pp.473-480
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• 1996

Automatic fatigue crack length measuring system using DC electrical potential method and the system control program for automatic fatigue testing under random load condition were made in this study. And using these system and control program, fatigue tests were executed under constant and random load condition. As the result, the propagation of crack in random loading can be represented Paris equaiton and log normal probability function. But constant and random load test show different crack propagation properties.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.6
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• pp.100-107
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• 1999

This paper describes a probabilistic remaining life assessment program for the creep crack growth. The probabilistic life assessment program is developed to increase the reliability of life assessment. The probabilistic life assessment involves some uncertainties, such as, initial crack size, material properties, and loading condition, and a triangle distribution function is used for random variable generation. The resulting information provides the engineer with an assessment of the probability of structural failure as a function of operating time given the uncertainties in the input data. This study forms basis of the probabilistic life assessment technique and will be extended to other damage mechanisms.

• Proceedings of the KWS Conference
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• 2007.11a
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• pp.245-247
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• 2007

Sn-base solder bump is mainly used in micro-joining for flip chip package. The quantity of intermetallic compounds that was formed between Cu pad and solder interface importantly affects reliability. In this research, micro-bump was fabricated by two binary electroplating and the intermetallic compounds(IMCs) was estimated quantitatively. When the micro Sn-Ag solder bump was made by electroplating, SiC powder was added in the plating solution for protecting of intermetallic growth. Then, the intermetallic compounds growth was decrease with increase of amount of SiC power. However, if the mount of SiC particle exceeds 4 g/L, the effect of the growth restraint decrease rapidly.

• International Journal of Highway Engineering
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• v.15 no.3
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• pp.93-101
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• 2013

PURPOSES : This study is to investigate the relationship of socioeconomic characteristics and road network structure with traffic growth patterns. The findings is to be used to tweak traffic forecast provided by traditional four step process using relevant socioeconomic and road network data. METHODS: Comprehensive statistical analysis is used to identify key explanatory variables using historical observations on traffic forecast, actual traffic counts and surrounding environments. Based on statistical results, a multiple regression model is developed to predict the effects of socioeconomic and road network attributes on traffic growth patterns. The validation of the proposed model is also performed using a different set of historical data. RESULTS : The statistical analysis results indicate that several socioeconomic characteristics and road network structure cleary affect the tendency of over- and under-estimation of road traffics. Among them, land use is a key factor which is revealed by a factor that traffic forecast for urban road tends to be under-estimated while rural road traffic prediction is generally over-estimated. The model application suggests that tweaking the traffic forecast using the proposed model can reduce the discrepancies between the predicted and actual traffic counts from 30.4% to 21.9%. CONCLUSIONS : Prediction of road traffic growth patterns based on surrounding socioeconomic and road network attributes can help develop the optimal strategy of road construction plan by enhancing reliability of traffic forecast as well as tendency of traffic growth.